Motivated by the realistic demand of reducing the flood risk of urban metro stations, this paper creatively proposes a research framework for flood risk classification assessment of metro stations. In the framework, a specified criterion system is established from the perspective of hazard, vulnerability, exposure and rescue capacity. Furthermore, a SMAA-2-FFS-H method is proposed, which is comprised of stochastic multi-criteria acceptability analysis-2 (SMAA-2), fuzzy flowsort (FFS) and multi-criteria hierarchy process (MCHP). For verifying the practicality and efficiency of the proposed framework, the flood risk evaluation of 32 stations in Zhengzhou Metro Line 5 during the "7·20" rainstorm event is taken as a case study. The results show that only Shakoulu Station is at high risk, which is correspond to the reality of the "7·20" rainstorm event. Moreover, the risk class characteristics of the remaining stations are correspond to historical flooding events. Among them, 10 metro stations are classified as medium risk, 21 metro stations are classified as low risk, and none metro station is classified as very low risk. As proved above all metro stations have a certain degree of flood risk, and the classes of flood risk are indeed different between some metro stations. In addition, the validity and robustness of the proposed method are demostrated by comparative analysis and sensitivity analysis. Finally, some managerial suggestions are provided for strengthening the flood control capacity of metro stations.
Motivated by the realistic demand of reducing the flood risk of urban metro stations, this paper creatively proposes a research framework for flood risk classification assessment of metro stations. In the framework, a specified criterion system is established from the perspective of hazard, vulnerability, exposure and rescue capacity. Furthermore, a SMAA-2-FFS-H method is proposed, which is comprised of stochastic multi-criteria acceptability analysis-2 (SMAA-2), fuzzy flowsort (FFS) and multi-criteria hierarchy process (MCHP). For verifying the practicality and efficiency of the proposed framework, the flood risk evaluation of 32 stations in Zhengzhou Metro Line 5 during the "7•20" rainstorm event is taken as a case study. The results show that only Shakoulu Station is at high risk, which is correspond to the reality of the "7•20" rainstorm event. Moreover, the risk class characteristics of the remaining stations are correspond to historical flooding events. Among them, 10 metro stations are classified as medium risk, 21 metro stations are classified as low risk, and none metro station is classified as very low risk. As proved above all metro stations have a certain degree of flood risk, and the classes of flood risk are indeed different between some metro stations. In addition, the validity and robustness of the proposed method are demonstrated by comparative analysis and sensitivity analysis. Finally, some managerial suggestions are provided for strengthening the flood control capacity of metro stations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.